One of the recommendations that came from the NIST investigation of the World Trade Center disaster was the need for quantitative heat flux measurements in larger scale fire safety tests. These heat flux data are needed to support the development of engineering models to predict the performance of fire protection materials and systems. Current standardized fire resistance tests such as ASTM E119 or ISO 834 or IMO A754 are all qualitative tests. The furnace temperature is controlled to a standard time-temperature curve. Implicit assumptions are made that (1) the thermal exposure can be described solely by the measured furnace temperature history and (2) that exposure will be repeatable. Historical variations of 50 % or more in the qualitative fire protection ratings, such as a 1 h fire barrier, between different furnaces or laboratories indicate that these two assumptions are not well founded. This paper describes the use of a proven type of sensor called a directional flame thermometer (DFT) for making quantitative heat flux measurements in fire resistance tests. DFTs have been used for over 20 years to characterize the thermal environment in both large pool fires and in furnaces, to monitor flashover in structure fires, and in many other fire environments. DFTs are passive thermocouple-based sensors. They do not require calibration. Instead, the designs and materials with known thermal properties are fixed to provide a repeatable response. Using inverse heat conduction analysis techniques, heat fluxes are calculated using a heat conduction model of the DFT with temperature-dependent thermal properties and two or more thermocouple temperature measurements in a DFT. A fully nonlinear inverse heat conduction code is used for detailed post-test data analysis. A new data analysis tool for DFTs, called an inverse heat conduction-digital filter functions (IHC-DFF) has been developed for specific DFT designs to provide heat flux measurements in real-time, much like a calibration curve. IHC-DFFs are convolution-type digital filters that are used to provide real-time heat flux readouts during a test or for a quick-look capability for large sets of data. Simpler models are also used for analyzing early (<5–10 min) and late-time DFT data (> 15 min). The current work demonstrates that DFT measurements can provide the quantitative data needed to support the development of performance models and improve our understanding of the thermal exposure in fire resistance tests.